Cognitive Processing Resource Allocation for Dynamic User Task Optimization
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Solution Overview
Problem
Computer systems face challenges in dynamically allocating computing resources based on user-specific tasks and usage patterns, leading to inefficient resource utilization across hardware components.
Innovation Solution
A processor runs a background process to identify users and analyze their interactions with applications, allocating computing resources such as CPUs, GPUs, or TPUs based on user identification, task type, and interaction analysis, potentially switching between resource allocation modes as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing resources are allocated uniformly to all hardware components, then system simplicity is maintained, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring user interactions and task types, then adjusting hardware resource distribution in real-time. The system transitions from static uniform allocation to dynamic contextual allocation, where resource distribution changes based on current usage patterns, achieving higher efficiency without requiring complex manual configuration.
Solution Approach 2:
The system performs self-adjustment by automatically analyzing user behavior patterns and task characteristics to determine optimal resource allocation. The background process continuously gathers interaction data, identifies task types, and autonomously modifies hardware resource distribution without user intervention, enabling the system to optimize itself based on observed usage patterns.
2Productivity
If resource allocation is dynamically adjusted based on user interactions, then resource utilization efficiency improves, but system response time increases
Solution Approach 1:
The system performs preliminary analysis of user interactions and task types in the background before resource allocation changes are needed. By continuously monitoring and pre-identifying task characteristics, the system prepares allocation decisions in advance, reducing the delay between detecting a task and implementing resource changes.
Solution Approach 2:
The system implements feedback mechanisms where user interactions are continuously monitored, analyzed, and used to adjust resource allocation. The background process receives feedback from user actions, identifies task patterns, and automatically modifies hardware resource distribution, creating a closed-loop system that adapts to usage patterns in real-time.
3Productivity
If user-specific resource allocation is implemented, then performance optimization improves, but power consumption increases
Solution Approach 1:
The patent applies local quality by tailoring hardware resource allocation to specific user tasks and interaction patterns rather than applying uniform resources to all operations. Different task types receive differentiated resource levels - high-performance tasks get more resources while routine tasks receive minimal resources, optimizing performance where needed while conserving power elsewhere.
Solution Approach 2:
The system dynamically changes resource allocation parameters based on detected task characteristics and user interaction patterns. By adjusting hardware resource distribution as a variable parameter responding to usage context, the system achieves performance optimization for demanding tasks while reducing power consumption for routine operations, balancing performance and energy efficiency.
Data Source
AI summary
A processor may run a background process to identify a first task being initiated by a first user on a device, where the first task is associated with a first application. The processor may identify the first user of the device. The processor may analyze one or more interactions of the first user associated with the first application on the device. The processor may allocate, based at least in part on identification of the first user, identification of the first task, or analysis of the one or more interactions of the first user, computing resources to one or more hardware components on the device.